DNA methylation analysis often looks routine — until coverage bias, over-smoothing, or platform-specific artifacts flatten meaningful signals and reduce biological confidence.

We help researchers fix these subtle but critical problems in bisulfite sequencing, array data, single-cell workflows, and multi-omics pipelines — ensuring high-confidence methylation insights that hold up under review.

🔍 Where Most Researchers Get Stuck:

• ❌ Normalization erases real biology
  Quantile normalization or over-smoothing can flatten meaningful group differences - especially in cancer or developmental data.
• ❌ Wrong tools, wrong assumptions
  Using DESeq2 or edgeR on bisulfite data breaks variance models and yields false confidence.
• ❌ Over-smoothing hides sharp signals
  Default pipelines often blur real regulatory boundaries - especially around enhancers and TSS.
• ❌ Nearest-gene assignment misleads
  Assigning DMRs to the closest TSS ignores chromatin loops and enhancer skipping.
• ❌ Array-specific traps go unnoticed
  SNP-overlapping probes, dye-channel biases, and multi-mapping artifacts require special care.
• ❌ Multi-omics mismatch
  Methylation and expression rarely align neatly. Interpreting discrepancies takes experience - not just correlation plots.
• ❌ Pipelines “run,” but don’t help
  Many published workflows look fine until results contradict the biology - or fail peer review.

DNA Methylation Analysis Services

Our DNA methylation analysis services provide robust bioinformatics support and deliver clear, publication-ready results. We help troubleshoot, interpret, and prepare figures and methods that hold up under peer review.

WGBS and RRBS Methylation Data Analysis

We perform coverage-aware WGBS and RRBS methylation analysis using adaptive smoothing and locus-level CpG calling tailored for variable coverage depths. Our region-level differential analysis applies robust statistics and generates clear, reproducible outputs suitable for publication and grant review.

EPIC Array Methylation Analysis

Our EPIC array analysis includes full QC, batch correction, dye-bias control, and probe filtering. We handle Illumina-specific pitfalls to deliver clean data ready for downstream integration with expression or phenotype data.

Single-Cell DNA Methylation Analysis

We provide single-cell methylation analysis and scBS-seq processing with methods designed for sparse coverage and cell-to-cell heterogeneity. Our workflows reconstruct high-confidence cell-specific methylomes and support integration with chromatin accessibility and expression data for comprehensive multi-omics interpretation.

DMR and Functional Methylation Annotation

Our pipelines deliver robust DMR annotation and functional interpretation that goes beyond simple nearest-gene mapping. By incorporating chromatin interaction maps, enhancer databases, and resources like FANTOM5, we provide regulatory context that standard tools often miss. When appropriate, we integrate expression and chromatin accessibility layers to clarify the functional impact of methylation changes.

✅ Why researchers trust our DNA methylation analysis:

- Coverage-aware WGBS and RRBS modeling
- EPIC array batch correction and probe QC
- Sparse data methods for single-cell methylomes
- Region-level differential calls and robust DMR annotation
- Clear, publication-ready figures and methods

Trusted by over 80 research institutions worldwide, with fast turnaround and publication-ready results.

📚 Learn More from Our Blog Series

• → DNA Methylation Analysis Isn’t Just Another Genomic Assay - Here’s What Often Goes Wrong
  A practical summary of real-world mistakes researchers make in WGBS, RRBS, and EPIC array analysis - from normalization to annotation.
• → Epigenomics Analysis: ATAC-seq, CUT&Tag, ChIP-seq, and DNA Methylation
  A cross-assay reflection on the hidden assumptions that quietly undermine interpretation in epigenomic studies - and how to catch them.

Explore the 10 Reasons Why Researchers Choose Us →

Reason #1: 150 years of combined experience in bioinformatics
Reason #2: Deep understanding of both the biology and the computer
Reason #3: Top-level expertise possessed by our bioinformaticians
Reason #4: Wide range of bioinformatics and data modeling solutions
Reason #5: Researchers from 80 organizations can’t all be wrong
Reason #6: We are cost-effective
Reason #7: We guarantee to do it “right”!
Reason #8: We will assist you in paper reviews
Reason #9: We will assist you in grant writing
Reason #10: See how researchers have evaluated us

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